The present invention relates to systems and methods for predicting traffic signal information, and for using the predicted traffic signal information to adjust the operation of an on-board system of a motor vehicle.
Related art motor vehicles may obtain real-time traffic flow information from various information providers, such as INRIX®. These information providers combine real-time road sensor data with real-time global positioning system (GPS) data from commercial and consumer vehicles in order to provide real-time traffic flow information. An on-board vehicle system may then apply simple decision-making capabilities, such as thresholds, in order to inform the driver of road or traffic conditions in the vicinity of the vehicle. For example, the on-board vehicle system may count the number of vehicles on a road segment to determine whether that segment should be displayed as green, yellow, or red on a navigation device within the vehicle. However, this analysis does not account for historical traffic data or predict the states of individual traffic signals in the vicinity of the motor vehicle.
A related art system described in U.S. Pat. No. 6,989,766 broadcasts real-time traffic signal data to a receiver in a vehicle. The traffic signal data may include the location, current status, future traffic signal sequences, and timing information of the traffic signal. The traffic signal data may be broadcast from individual traffic signals or a central location that gathers and stores traffic signal data from multiple traffic signals. Based on the received traffic signal data, the vehicle may display a speed range that minimizes the number of starts and stops that are required and facilitates traffic flow.
Similarly, the Audi® Travolution® project uses an on-board system that receives real-time traffic signal data from individual traffic signals via dynamic short-range communication (DSRC) and provides speed recommendations to the driver. The system may also provide time-to-green and time-to-red information to the driver. However, the system does not make predictions for the traffic signals, and therefore can only provide recommendations that account for traffic lights within the short DSRC range.
In addition, Green Driver® provides a mobile telephone application that predicts the states of traffic signals based on real-time traffic signal information from a traffic center. The application calculates the speed required to pass through a traffic light before it turns red, and provides suggested routes to avoid red lights. However, Green Driver® makes predictions over a short distance, not for all traffic lights along a route to a destination. Further, the application is not integrated with the vehicle, and does not incorporate vehicle-specific information into the speed calculations.
Further, SignalGuru® uses crowdsourced data to detect and predict the traffic signal schedule. SignalGuru® uses windshield-mounted mobile telephones to acquire real-time images of traffic signals and determine the color of the traffic signal. The system analyzes data acquired from other vehicles to recommend when drivers should reduce their speed to avoid idling at a red light. The system may also recommend a detour to provide a more efficient route to a destination. However, SignalGuru® relies solely on inferior images acquired from mobile telephone cameras and problematic image analysis techniques.
Therefore, it would be desirable to provide an improved system and method for predicting traffic signal information that utilizes data from more than one source, and that uses advanced models and machine learning techniques that consider historical data. It would also be desirable to use the predictive traffic signal information to adjust the operation of an on-board system of a vehicle, particularly an on-board system that can improve fuel consumption and reduce harmful emissions.